An Expectation Maximisation Algorithm for ...
Type de document :
Communication dans un congrès avec actes
Titre :
An Expectation Maximisation Algorithm for Behaviour Analysis in Video
Auteur(s) :
Isupova, Olga [Auteur]
University of Sheffield [Sheffield]
Mihaylova, Lyudmila [Auteur]
University of Sheffield [Sheffield]
Kuzin, Danil [Auteur]
University of Sheffield [Sheffield]
Markarian, Garik [Auteur]
Lancaster University
Septier, Francois [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
University of Sheffield [Sheffield]
Mihaylova, Lyudmila [Auteur]
University of Sheffield [Sheffield]
Kuzin, Danil [Auteur]
University of Sheffield [Sheffield]
Markarian, Garik [Auteur]
Lancaster University
Septier, Francois [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Titre de la manifestation scientifique :
Int. Conf. on Information Fusion (FUSION)
Ville :
Washington D.C.
Pays :
Etats-Unis d'Amérique
Date de début de la manifestation scientifique :
2015-07-06
Date de publication :
2015-07-06
Discipline(s) HAL :
Sciences de l'ingénieur [physics]/Traitement du signal et de l'image [eess.SP]
Résumé en anglais : [en]
Surveillance systems require advanced algorithms able to make decisions without a human operator or with minimal assistance from human operators. In this paper we propose a novel approach for dynamic topic modeling to ...
Lire la suite >Surveillance systems require advanced algorithms able to make decisions without a human operator or with minimal assistance from human operators. In this paper we propose a novel approach for dynamic topic modeling to detect abnormal behaviour in video sequences. The topic model de- scribes activities and behaviours in the scene assuming behaviour temporal dynamics. The new inference scheme based on an Expectation-Maximisation algorithm is implemented without an approximation at intermediate stages. The proposed approach for behaviour analysis is compared with a Gibbs sampling inference scheme. The experiments both on synthetic and real data show that the model, based on Expectation-Maximisation approach, outperforms the one, based on Gibbs sampling scheme.Lire moins >
Lire la suite >Surveillance systems require advanced algorithms able to make decisions without a human operator or with minimal assistance from human operators. In this paper we propose a novel approach for dynamic topic modeling to detect abnormal behaviour in video sequences. The topic model de- scribes activities and behaviours in the scene assuming behaviour temporal dynamics. The new inference scheme based on an Expectation-Maximisation algorithm is implemented without an approximation at intermediate stages. The proposed approach for behaviour analysis is compared with a Gibbs sampling inference scheme. The experiments both on synthetic and real data show that the model, based on Expectation-Maximisation approach, outperforms the one, based on Gibbs sampling scheme.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
Source :